Structural Equation Models [electronic resource] : From Paths to Networks /
Westland, J. Christopher.author.(orcid)0000-0003-2224-4543https://orcid.org/0000-0003-2224-4543aut
This compact reference surveys the full range of available structural equation modeling (SEM) methodologies.  It reviews applications in a broad range of disciplines, particularly in the social sciences where many key concepts are not directly observable.  This is the first book to present SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method.  This book also surveys the emerging path and network approaches that complement and enhance SEM, and that will grow in importance in the near future.  SEM’s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists.  Latent variable theory and application are comprehensively explained, and methods are presented for extending their power, including guidelines for data preparation, sample size calculation, and the special treatment of Likert scale data.  Tables of software, methodologies and fit statistics provide a concise reference for any research program, helping assure that its conclusions are defensible and publishable.
Description based upon print version of record.
Includes bibliographical references and index.
An Introduction to Structural Equation Models -- A Brief History of Structural Equation Models -- Partial Least Squares Path Analysis -- LISREL and its Progeny -- Systems of Regression Equations -- Data Collection, Control and Sample Size -- Survey and Questionnaire Data -- Research Structure and Paradigms -- From Paths to Networks: The Evolving Science of Networks.
This compact reference surveys the full range of available structural equation modeling (SEM) methodologies.  It reviews applications in a broad range of disciplines, particularly in the social sciences where many key concepts are not directly observable.  This is the first book to present SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method.  This book also surveys the emerging path and network approaches that complement and enhance SEM, and that will grow in importance in the near future.  SEM’s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists.  Latent variable theory and application are comprehensively explained, and methods are presented for extending their power, including guidelines for data preparation, sample size calculation, and the special treatment of Likert scale data.  Tables of software, methodologies and fit statistics provide a concise reference for any research program, helping assure that its conclusions are defensible and publishable.
Computational intelligence.
Statistics .
Physics.
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Industrial management.
Psychometrics.
Engineering geology.
Engineering—Geology.
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Computational Intelligence.
Statistics for Social Sciences, Humanities, Law.
Applications of Graph Theory and Complex Networks.
Innovation/Technology Management.
Psychometrics.
Geoengineering, Foundations, Hydraulics.